Supporting Hyperplanes

Related lectures (29)

Page 3 of 3

Explores directional derivatives, tangent planes, and function differentiability in multivariable calculus.

Explores differentiable functions in R², including vector fields and coordinate transformations.

Covers the representation of differentiable functions in R² and the concept of changes of coordinates through bijections.

Covers vector spaces, differentiable functions, scalar product, and norms in depth.

Explores differentiability, tangent planes, and algebraic derivatives in functions of two variables.

Covers the concept of approximating a function around a point xo using linear approximation.

Discusses proximal gradient descent and its applications in optimizing machine learning algorithms.

Provides an overview of optimization techniques, focusing on gradient descent and properties of convex functions in machine learning.

Explores integration by substitution technique with examples and verification.